_toc.yml

format: jb-book
root: index

parts:
- chapters:
  - url: https://www.bpesquet.fr/mlkatas
    title: Machine Learning Katas
- caption: overview
  chapters:
  - file: overview/introduction_to_machine_learning
  - file: overview/machine_learning_in_action
  - file: overview/introduction_to_reinforcement_learning
- caption: Fundamentals
  chapters:
  - file: fundamentals/handling_data
  - file: fundamentals/assessing_results
  - file: fundamentals/training_models
- caption: Algorithms
  chapters:
  - file: algorithms/classic_ml
    sections:
    - file: algorithms/k_nearest_neighbors.ipynb
    - file: algorithms/linear_regression
    - file: algorithms/logistic_regression
    - file: algorithms/decision_trees_and_random_forests
    - file: algorithms/bayesian_methods
    - file: algorithms/support_vector_machines
    - file: algorithms/k_means
  - file: algorithms/nn_deep_learning
    sections:
    - file: algorithms/artificial_neural_networks
    - file: algorithms/convolutional_neural_networks
    - file: algorithms/recurrent_neural_networks
    - file: algorithms/autoencoders
    - file: algorithms/neural_style_transfer
    - file: algorithms/generative_adversarial_networks
    - file: algorithms/transformers
- caption: Engineering
  chapters:
  - file: engineering/introduction_to_mlops
  - file: engineering/machine_learning_issues
- caption: Tools
  chapters:
  - file: tools/python
    sections:
    - file: tools/python_ecosystem
    - file: tools/python_cheatsheet
    - file: tools/python_good_practices
  - file: tools/numpy
  - file: tools/keras
  - file: tools/pytorch
- caption: Reference
  chapters:
  - file: reference/activation_functions
  - file: reference/glossary
  - file: reference/acknowledgments